.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/fusion_extraction.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_gallery_fusion_extraction.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_gallery_fusion_extraction.py:


Designing fusion network to generate resource graph state
==========================================================

In this example, we decompose a graph state into a set of GHZ and linear cluster resource states,
such that fusion operations can be used on these 'micro-resource' states to obtain the desired graph state.
This is an important compilation stage to perform MBQC on discrete-variable optical QPUs.

The decomposition algorithm is based on [1].

[1] Zilk et al., A compiler for universal photonic quantum computers,
2022 `arXiv:2210.09251 <https://arxiv.org/abs/2210.09251>`_

.. GENERATED FROM PYTHON SOURCE LINES 17-25

.. code-block:: Python

    from __future__ import annotations

    import itertools

    import graphix
    from graphix import extraction
    from graphix.extraction import graph_to_fusion_network








.. GENERATED FROM PYTHON SOURCE LINES 26-28

Here we say we want a graph state with 9 nodes and 12 edges.
We can obtain resource graph for a measurement pattern by using :code:`pattern.extract_graph()`.

.. GENERATED FROM PYTHON SOURCE LINES 28-35

.. code-block:: Python

    gs = graphix.GraphState()
    nodes = [0, 1, 2, 3, 4, 5, 6, 7, 8]
    edges = [(0, 1), (1, 2), (2, 3), (3, 0), (3, 4), (0, 5), (4, 5), (5, 6), (6, 7), (7, 0), (7, 8), (8, 1)]
    gs.add_nodes_from(nodes)
    gs.add_edges_from(edges)
    gs.draw()




.. image-sg:: /gallery/images/sphx_glr_fusion_extraction_001.png
   :alt: fusion extraction
   :srcset: /gallery/images/sphx_glr_fusion_extraction_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 36-37

Decomposition with GHZ and linear cluster resource states with no limitation in their sizes.

.. GENERATED FROM PYTHON SOURCE LINES 37-39

.. code-block:: Python

    graph_to_fusion_network(gs)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    [ResourceGraph(cltype=<ResourceType.GHZ: 'GHZ'>, graph=<graphix.graphsim.GraphState object at 0x753cdae40350>), ResourceGraph(cltype=<ResourceType.GHZ: 'GHZ'>, graph=<graphix.graphsim.GraphState object at 0x753cdae40790>), ResourceGraph(cltype=<ResourceType.LINEAR: 'LINEAR'>, graph=<graphix.graphsim.GraphState object at 0x753cdb13e990>)]



.. GENERATED FROM PYTHON SOURCE LINES 40-46

If you want to know what nodes are fused in each resource states,
you can use :func:`~graphix.extraction.get_fusion_nodes` function.
Currently, we consider only type-I fusion. See [2] for the definition of fusion.

[2] Daniel E. Browne and Terry Rudolph. Resource-efficient linear optical quantum computation.
Physical Review Letters, 95(1):010501, 2005.

.. GENERATED FROM PYTHON SOURCE LINES 46-53

.. code-block:: Python

    fused_graphs = graph_to_fusion_network(gs)
    for idx1, idx2 in itertools.combinations(range(len(fused_graphs)), 2):
        print(
            f"fusion nodes between resource state {idx1} and "
            f"resource state {idx2}: {extraction.fusion_nodes(fused_graphs[idx1], fused_graphs[idx2])}"
        )





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    fusion nodes between resource state 0 and resource state 1: [1]
    fusion nodes between resource state 0 and resource state 2: [7, 5, 3]
    fusion nodes between resource state 1 and resource state 2: [2, 8]




.. GENERATED FROM PYTHON SOURCE LINES 54-56

You can also specify the maximum size of GHZ clusters and linear clusters available,
for more realistic fusion scheduling.

.. GENERATED FROM PYTHON SOURCE LINES 56-57

.. code-block:: Python

    graph_to_fusion_network(gs, max_ghz=4, max_lin=4)




.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    [ResourceGraph(cltype=<ResourceType.GHZ: 'GHZ'>, graph=<graphix.graphsim.GraphState object at 0x753cf340e610>), ResourceGraph(cltype=<ResourceType.GHZ: 'GHZ'>, graph=<graphix.graphsim.GraphState object at 0x753cdaef10d0>), ResourceGraph(cltype=<ResourceType.LINEAR: 'LINEAR'>, graph=<graphix.graphsim.GraphState object at 0x753cdb3f9450>), ResourceGraph(cltype=<ResourceType.LINEAR: 'LINEAR'>, graph=<graphix.graphsim.GraphState object at 0x753cdb3faa90>)]




.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.048 seconds)


.. _sphx_glr_download_gallery_fusion_extraction.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: fusion_extraction.ipynb <fusion_extraction.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: fusion_extraction.py <fusion_extraction.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: fusion_extraction.zip <fusion_extraction.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_